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How Does Clickbait Work: an Eye-Tracking Method to Discover People’S Reactions

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How Does Clickbait Work: an Eye-Tracking Method to Discover People’S Reactions How does clickbait work: An eye-tracking method to discover people’s reactions Student Name : Yiteng Xing Date : 19th September 2016 Supervisor : Dr. Alistair Edwards Word count : 12312 Submitted in partial fulfillment of the requirements for the degree of Master of Science in Human-Centred Interactive Technologies in the Department of Computer Science at the University of York Number of words = 12312, as counted by the MS Word word count command. This includes all the body of the report, but excludes Appendix. 1 ABSTRACT Clickbait web content is designed to entice people into clicking on a link. The publishers use strategies in writing headlines in order to create a ‘curiosity gap’ between the content and the reader. However, this bait often tricks people into clicking and leaves them disappointed. As a growing number of people are getting information through online media platforms, it is necessary to discover how clickbait works and which elements induce people to click on it. In this paper, we designed a lab-based experiment to observe the participant’s reaction to clickbait by using screen recording and eye-tracking mechanisms. A qualitative research method with two coding schemes was applied to 151 headlines which were clicked by 20 participants. The results show that people are attracted by clickbait headlines that contain elements of ‘a list’, ‘game’, ‘celebrity’ and ‘You or I’. However, the result changes slightly based on the different types of user. Then, the clickbait working principle, effectiveness of the eye-tracking method and the limitations of this study are discussed. In addition, this study contributes to further work by generating sufficient categorisation for clickbait and more specific research can be conducted such as clickbait with culture, language and social network sharing. 2 ACKNOWLEDGEMENTS I would like to express my deepest appreciation to all those who provided me with the chance to complete this report. I would especially like to thank my project supervisor, Dr. Alistair Edwards, who gave me very detailed suggestions every week over the past five months and helped me to coordinate my project, particularly in writing this report. I would also like to extend my deepest gratitude to all those who have directly and indirectly guided us in writing this assignment. Many people, especially some of our HCI group team members – Professor Helen Petrie, Mr. Leonardo Guzman and Mr. Andrew Lewis, have made valuable comments or suggestions on the experiment, which gave me the inspiration to improve this paper. I also appreciate the University of York for providing me with the eye tracker to complete the experiment. I sincerely thank everyone for their direct and indirect help in completing my final project. 3 CONTENTS ABSTRACT…………………………………………………………………………. 2 ACKNOWLEDGEMENTS…………………………………………………………. 3 LIST OF TABLES…………………………………………………………………... 5 LIST OF FIGURES…………………………………………………………………. 6 CHAPTER 1: Introduction…………………………………….……......................... 7 CHAPTER 2: Literature Review………………………………………………….... 12 CHAPTER 3: Methodology…………………............................................................26 CHAPTER 4: Result…………................................................................................... 40 CHAPTER 5: Discussion………………………………………………….…...…... 53 CHAPTER 6: Conclusion…………………………………………………….…….. 66 REFERENCES……………………………………………………………...……….68 APPENDIX A: Consent Form……………………………………………………….74 APPENDIX B: Information Sheet…………………………………………….…..…76 APPENDIX C: Debriefing Sheet………………………………………………….…79 4 LIST OF TABLES Table 1. First coding scheme of 151 headlines with images………………….….. 37 Table 2. Second coding scheme of 151 headlines with images……………....……37 Table 3. Overview of coding data with occurrence and percentage………….…... 41 Table 4. Percentage of different click preferences between male and female……..43 Table 5. Percentage of different click preferences between two age groups..….….45 Table 6. Overview of the second coding result…………………………...…..…... 47 Table 7. Comparison of Non-clickbait and clickbait headlines based on number of coding elements per title……………………………………………………….…..48 Table 8. Overall comparison between Section 1 and Section 3………………...….49 Table 9. Gender group click preference comparison between Section 1 and Section 3……………………………….……………………………………………….…..51 Table 10. Gender group click preference comparison between Section 1 and Section 3…………………………………………………………………………………...….52 5 LIST OF FIGURES Figure 1. News (a) and Clickbait (b) headline formats…………………………….….8 Figure 2. A click through rate comparison between two types of advertisement….... 25 Figure 3. Percentage of Headlines that contain these 19 Coding Elements…….…... 41 Figure 4. Percentage of different click preferences between male and female.……...43 Figure 5. Percentage of different click preferences between two age groups...…..….46 Figure 6. Overview of the second coding result…………………………...…....…... 47 Figure 7. Comparison of Non-clickbait and clickbait headlines based on number of coding elements per title………………………………………………………….…..48 Figure 8. Overall comparison between Section 1 and Section 3……………….....….50 6 CHAPTER 1 Introduction One of the most important considerations for online journalists is attracting a reader’s attention through headlines alone. Without interest in a headline, there will be no interest in the story. By enticing a reader to click on a catchy headline, there is a high click rate for the website, which leads to advantages for the website owners. There are various stances that journalists take in trying to grab a person’s attention. Schaffer notes the use of gossip-like content that highlights aspects such as scandal, sex, heartbreak, or even maximising on interest of the supernatural [1]. Similarly, Molek-Kozakowska and Wallberg identify the role of sensationalism and provocation in these headlines. It does not purely come down to content [2] [3], however; Lindemann notes the use of narrative techniques to increase the appeal of a headline [4]. Ultimately, if a headline does not capture a reader’s attention, then they will not be driven to read the entire article, so headlines must be particularly clever or alluring. This has always been a generally accepted fact, however the widespread use of the Internet in modern society has 7 created an even more important need to draw in a reader through catchy headlines, known as “clickbait”. Figure 1 below demonstrates examples of ‘Clickbait’, described as a “sensationalised headline or piece of text on the Internet designed to entice people to follow a link to an article on another web page” [5]. Clickbait is often misrepresentative and therefore risks spreading distortion of truth. For example, Figure 1 compares two headlines written on the same news piece, the publication of Michelle Obama’s biography. It can clearly be seen how (b) has chosen to highlight the salacious aspects of the story whereas (a) takes a more academic approach. Figure 1. News (a) and Clickbait (b) headline formats [5] 8 The widespread adoption of this style of journalism is already under criticism, that is, the seemingly sensationalised tabloid-style approach, and online clickbait is perceived to be even more dangerous [5]. Clickbait headlines condense certain aspects of a story, maximising manipulation of fact and using word-of-mouth as gospel. Although this approach clearly entices readers, it perpetuates gossip and mistruth, and journalistic integrity becomes ever weakened. The internet is a dangerous medium for news; stories are presented as an ensemble in “streams” so that reputable and non- reputable sources are mixed together and headlines are taken out of context [6]. Chen, Conroy and Rubin criticised Facebook for this presentation of news; online, news spreads quickly therefore rumours and warped truths can cause huge damage [5]. Consequently, Blom and Hansen call for clickbait to be analysed in terms of ethics rather than how much money it can generate [7]. Clickbait can be understood in terms of Chen, Conroy and Rubin’s concept of “sense making metaphors” [5], which are used in the study of Library and Information Science to uncover how interest in a subject is at once created and fulfilled, as with clickbait [8]. Readers are given an intense sentiment of intrigue, not wanting to be disappointed in this quest for discovery and seek fulfilment for their desire for information by looking at more articles [9]. Clickbait headlines feed on this drive for knowledge, tempting readers to discover the full story through small, intriguing aspects. These features could be utilised by information systems 9 to detect lowbrow clickbait news. Indeed, former studies have attempted to introduce automatic systems to authenticate news, but have yet to do so for clickbait [5]. Chen, Conroy and Rubin discuss how connections are made between pieces of information to create a gap in understanding of a subject, and then fill that gap [5]. Sense making metaphors are essential considerations in understanding how intrigue is created by clickbait headlines and the lexical choices made. However, getting more clicks and thereby more visits on websites ultimately amounts to one thing: these websites can raise their advertising rates and make profit [10]. Publishers often incentivise their writers to get clicks on stories, which can lead to the simplification of articles and headlines for monetary gain [10]. Slant, an online magazine, pays writers $5 for every 500 clicks on a story on top of their monthly
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